Detection and Segregation of Plastic Waste using a Robotic Arm.

Plastic waste pollution has become one of the most significant environmental concerns in recent years. The accumulation of plastic waste has been observed in various locations worldwide, leading to environmental damage and health hazards. In this paper, a system is proposed for the detection and segregation of plastic waste using a Robotic arm manipulator based on YOLOv5 and Raspberry Pi. YOLOv5 is an advanced object detection algorithm that can identify plastic waste in images. The Raspberry Pi is a low-cost, small-sized computer that can be used as the central processing unit for the proposed system. The system includes a camera module that captures images of the waste material in real time, and an ultrasonic sensor to measure distance of the object. It detects and identifies the plastic waste in the image. Then, using the 3-D coordinate values calculated from the data gathered from the camera and ultrasonic sensor, plastic waste is separated using a robotic arm by applying inverse kinematics, controlled by the Raspberry Pi. The proposed system's performance was evaluated using various custom datasets, and the results show that it can effectively detect and segregate plastic waste from other types of waste materials. [ABSTRACT FROM AUTHOR]